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Record W4293212291 · doi:10.1002/dta.3361

Addressing recent challenges in isotope ratio mass spectrometry: Development of a method applicable to 1‐androstene‐steroids, 6α‐hydroxy‐androstenedione, and androstatrienedione

2022· article· en· W4293212291 on OpenAlexfundno aff
Thomas Piper, Mario Thevis

Bibliographic record

VenueDrug Testing and Analysis · 2022
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersBundesministerium des Innern, für Bau und HeimatWorld Anti-Doping Agency
KeywordsIsotope-ratio mass spectrometryChemistryChromatographyAnalyteMetaboliteEpitestosteroneAnabolismMass spectrometryHigh-performance liquid chromatographySteroidHormoneBiochemistry

Abstract

fetched live from OpenAlex

In 2020, the confirmation of the non-endogenous origin of several pseudo-endogenous steroids by means of isotope ratio mass spectrometry (IRMS) was recommended by the World Anti-Doping Agency (WADA), in addition to previously established target analytes for IRMS in sports drug testing. To date, however, IRMS-based methods validated in accordance with current WADA regulations have not been available. Therefore, the aim of this research project was the development and validation of a method to determine the carbon isotope ratios (CIR) of all newly considered pseudo-endogenous steroids, encompassing the anabolic androgenic steroids comprising a 1-ene-core structure (5α-androst-1-ene-3β,17β-diol, 5α-androst-1-ene-3,17-dione [1AD], 17β-hydroxy-5α-androst-1-en-3-one, 3α-hydroxy-5α-androst-1-ene-17-one [1AND], and 3β-hydroxy-5α-androst-1-ene-17-one [1EpiAND]), as well as steroids referred to as hormone and metabolic modulators (androsta-1,4,6-triene-3,17-dione [TRD] and its main metabolite 17β-hydroxy-androsta-1,4,6-triene-3-one) and 6α- and 6β-hydroxy-androst-4-ene-3,17-dione. With peak purity of target analytes being critical for IRMS analyses, a twofold high-performance liquid chromatography (HPLC)-based sample purification was employed, with all analytes being acetylated between the first and second HPLC fractionation. Using established gas chromatography/combustion/IRMS instrumentation, limits of quantification were estimated at 10 ng/ml for a 20 ml urine aliquot for all analytes, except for 1AND (20 ng/ml), and combined measurement uncertainties were estimated between 0.4‰ and 0.9‰. For proof-of-concept, samples collected after the single oral administration of a nutritional supplement containing 1AD and 1EpiAND were analyzed as well as existing excretion study urine samples obtained after the administration of 4-androstenedione and TRD. Based on the obtained results, the developed method was considered to be fit-for-purpose.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.085
GPT teacher head0.320
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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